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Management of Pancreatic Cystic Lesions Using Artificial Intelligence Based on EUS and Multimodal Data
Sponsor: Huazhong University of Science and Technology
Summary
The primary objective is to construct a multimodal AI model (Cyst-AI) based on EUS images and clinical data such as imaging features(CT or MRI) and laboratory tests to assist endoscopists in the diagnosis of pancreatic cystic lesions(PCLs), mainly differentiating mucinous from non-mucinous lesions. The secondary objective is to evaluate the model's effectiveness in risk stratification and clinical management for patients with PCLs.
Official title: A Multimodal Artificial Intelligence Model for Subtyping Diagnosis and Clinical Management of Pancreatic Cystic Lesions Based on Endoscopic Ultrasound and Clinical Information
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
500
Start Date
2025-01-01
Completion Date
2026-06
Last Updated
2026-03-11
Healthy Volunteers
No
Conditions
Interventions
Cyst-AI model
The multi-center collected data will be divided into a training set, a validation set, and a test set for developing and testing the cyst-AI model.
Locations (2)
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, Hubei, China
Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology
Wuhan, Hubei, China